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Stingray Submission #201

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@matteobachetti

Description

@matteobachetti

Submitting Author: @matteobachetti
All current maintainers: @dhuppenkothen, @mgullik, @jdswinbank, @matteolucchini1
Package Name: Stingray
One-Line Description of Package: A spectral-timing software package for astrophysical X-ray (and other) data
Repository Link: https://github.com/stingraysoftware/stingray

Version submitted: 2.1
EiC: @cmarmo
Editor: @hamogu
Reviewer 1: @taldcroft
Reviewer 2: @masonng-astro
Archive: DOI
JOSS DOI: 10.21105/joss.07389
Version accepted: 2.1
Date accepted (month/day/year): 10/01/2024


Code of Conduct & Commitment to Maintain Package

Description

  • Include a brief paragraph describing what your package does:

Stingray is a Python library for "spectral timing", i.e. time-series analysis techniques that can be used to study how variability changes or correlates between different energy bands/wavelengths. It is Astropy-affiliated, and with an ever growing user base now comprising hundreds of researchers around the globe.

Scope

  • Please indicate which category or categories.
    Check out our package scope page to learn more about our
    scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

    • Data retrieval
    • Data extraction
    • Data processing/munging
    • Data deposition
    • Data validation and testing
    • Data visualization1
    • Workflow automation
    • Citation management and bibliometrics
    • Scientific software wrappers
    • Database interoperability

Domain Specific

  • Geospatial
  • Education

Community Partnerships

If your package is associated with an
existing community please check below:

  • For all submissions, explain how and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):

This package is mostly focused on the analysis of new data from high-energy missions. We added data validation and testing because it can be used as a quick look tool to point out possible anomalies in observations (e.g. solar or other background flares).

  • Who is the target audience and what are scientific applications of this package?

The target audience is principally researchers and students of X-ray and multi-wavelength astronomy.
This package fills a void for a free and open source (spectral-)timing package for X-ray astronomy. XRONOS, formerly maintained by HEASARC, is currently unmaintained, and the analysis of high-energy timeseries is done mostly with proprietary software or mission-specific packages. We provide a Python package that eases the learning curve for newcomers, also thanks to extensive tutorials based on Jupyter notebooks, and provides experts with a powerful, robust library for their analysis. We provide software to analyze astronomical time series and do a number of things, including periodicity searches, time lag calculations, covariance spectra, power spectral modeling.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?

Our package is arguably the most well-known Python package for X-ray spectral timing.

  • If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

#195

Technical checks

For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:

  • does not violate the Terms of Service of any service it interacts with.
  • uses an OSI approved license.
  • [ x contains a README with instructions for installing the development version.
  • includes documentation with examples for all functions.
  • contains a tutorial with examples of its essential functions and uses.
  • has a test suite.
  • has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

Publication Options

JOSS Checks
  • The package has an obvious research application according to JOSS's definition in their submission requirements. Be aware that completing the pyOpenSci review process does not guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
  • The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
  • The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/. We have a previous JOSS paper describing the package. Is it acceptable to have a new paper, including the many improvements made in the last five years?
  • The package is deposited in a long-term repository with the DOI:

Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.

Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?

This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.

  • Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.

Confirm each of the following by checking the box.

  • I have read the author guide.
  • I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

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Footnotes

  1. Please fill out a pre-submission inquiry before submitting a data visualization package.

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